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As I see it, programming questions tend to take one of two forms:

1. How do I do X?
2. How do I do X in a clean, maintainable, and elegant way?

Matt Gemell has a great response to questions of the first form. I have nothing to add to his excellent post on that topic.

But I think it's crucially important to make a distinction between the two forms. The second form is a far more difficult question, asked far less commonly, and to which good answers are even rarer. When questions of this form are asked in forums, people are usually given a link to a page describing a pattern, or if they are really "lucky" a page with a sample implementation of that pattern. To be fair, patterns usually are the answer to these types of questions. But what we find written up on the web, or even in books, is most commonly pathetically oversimplified, without context, and often even without guidance on what support patterns are necessary to obtain the benefit or when alternatives may be preferable.

Essentially, most developers are left with no choice but to apply Matt's answer to form 1, to questions of form 2, in a much less information-rich environment. I contend that, while it may be one of those proverbial activities that "build character", it is ultimately more likely to be harmful to their immediate productivity--possibly even to their continued professional growth.

What we end up with is a pandemic of developers trying to hack out pattern implementations, being discouraged by the fact that the pattern seems to have no accounting for any possible deviations or complications in the form of the problem. Worse, developers are often dismayed to find that the one pattern they were told to use is merely the tip of a huge iceberg of support patterns without which the first may actually be more problematic than an ad hoc solution. Most often the developer in this position will end up determining that their deadlines will never allow them to go through the painful trial and error process on every one of these patterns, and accordingly drop back to the ad hoc solution.

It's time that we acknowledge that software development, whether you consider it an engineering discipline, an art, or a craft, has a history--albeit a short one. Things have been tried. Some work, some don't. There do exist "solved problems" in our problem space. To say that every developer should try and fail at all these efforts on their own ignores and devalues the collective experience of our community. Worse, it stunts the growth of the software development industry as a whole.

Yes, one can learn these things by trial and error. Yes, the understanding gained in this way is deeper and stronger than that gained initially by being tutored on how to apply the solution. And yes, there's a certain pride that comes with getting things done in this way. But this is not scalable. Putting each person forcibly through this crucible is not a sustainable strategy for creating experienced, productive, wise programmers. Every hour spent grappling in isolation with a question of "why won't this pattern do what I've been told it will" is an hour that could be spent creating functionality, or heaven forbid solving a new problem.

That is why those of us who have managed to obtain understanding of these "solved problems" must be willing to shoulder the responsibility of mentoring the less experienced. Being willing to explain, willing to discuss specifics, mutations, deviations, exceptions. Willing to discus process, mindset, methodology. These are the things that make the distinction between a programmer and a software developer, between a software developer and a software engineer.

The internet may very well not be the appropriate place to seek or provide this type of mentoring. I suspect it's not. And unfortunately, there are too many development teams out there buried in companies whose core competencies are not software, and consisting solely of these discouraged developers, lacking an experienced anchor, or even a compass. There are online communities that attempt to address the problem at least partially. ALT.NET is one such, for .NET technologies. But there really is no substitution for direct, personal mentorship.

So I would encourage young developers out there to seek out more experienced developers, and ask them the tough, form 2 questions. And I would even more strongly encourage experienced developers to keep a watchful eye for those in need of such guidance. Maybe even consider proactively forming a local group and seeking out recruits. Be willing, able, and happy to provide this guidance, because it benefits all of us. Every developer you aid is one less developer creating an ad hoc solution which you or I will be condemned to maintain, overhaul, or triage somewhere down the line.

Incidental Redundancy

A note: I originally composed this blog post in June 2008, but lost it in my backlog and it never got posted. In the interim, Robert C. "Uncle Bob" Martin has addressed the issue in his Clean Code Tip of the Week #1. He describes the issue and the dilemma far more concisely than I have here, and even provides a strategy for dealing with it. By all means feel free to skip my post here and consider him the "official source" on this topic. =)

I am a big fan of "lazy programming". By that of course I mean avoiding repetition and tedium wherever possible. I mean, that's what most programming is really about, right? You have a problem: some process that is annoying, unwieldly, or even impossible to perform with existing tools. And the solution is to write a program that takes care of all the undesirable parts of that process automatically, based on a minimized set of user input or configuration data.

The realities of programming on an actual computer rather than in an idealized theoretical environment rarely allow this ascending staircase of productivity to be climbed to the top step. But it is nevertheless a goal we should always strive for.

Hence Jeff Atwood's recent post about eliminating redundancies.

Anything that removes redundancy from our code should be aggressively pursued

An honorable goal, to be sure. But no rule is without exception, right?

I humbly submit to you the concept of "incidental redundancy". Incidental redundancy is a repetition of code syntax or semantics that tempts the programmer to refactor, but if carried out the refactoring could damage the elegance and discoverability of the program.

The difference between incidental redundancy and regular redundancy in code is that the redundancy does not arise because of any substantive, or at least relevant, similarity between the two problems in question. Here are two ways I can think of off the top of my head for this to happen:

1. The solutions you have come up with to this point for each situation just happen to have taken a similar form. Given a different creative whim, or even just an alternative refactoring, the commonality may never have arisen.
2. The problems are, in fact, similar at some level. But the level at which they are similar is far above or below the level where you are working, and so not truly relevant or helpful to the immediate problems you are trying to solve.

The first situation should be acceptable enough to anyone who has spent a decent amount of time programming. Sooner or later, you will spend some precious time carefully crafting a solution to a problem only to later discover that a year and a half previous, you had solved the same exact problem, in a completely different and maybe even better way.

The second situation may sound a little incredible. But allow me to point out an example from the world of physics. Please bear with me as this is an area of personal interest, and it really is the best example that comes to mind.

There are four forces in the known universe which govern all interactions of matter and energy, at least one of which I'm sure you've heard of: the electromagnetic, weak nuclear, strong nuclear, and gravitational forces. It is known now that the first two of those apparently very different forces are in fact two different aspects of the same phenomenon (the electroweak force), which only show up as different when ambient temperature is comparatively low. Most physicists are pretty sure that the third force is yet another aspect of that same phenomenon that splits off only at even higher temperatures. And it is suspected that gravity can be unified with the rest at temperatures higher still.

The point of all this is that there are four different phenomena which in fact bear undeniable similarities in certain respects, and these similarities continue to drive scientists to create a generalized theory that can explain it all. But no one in his right mind would try to design, for example, a complex electrical circuit based entirely on the generalized theory of the electroweak force.

The analogy to programming is that, were we to try to shift up to that higher level and formulate an abstraction to remove the redundancy, the effect on the problem at hand would be to make the solution unwieldly, or opaque, or verbose, or any number of other undesirable code smells. All at the cost of removing a little redundancy.

What we have in both physics and in our programming dilemma, is noise. We are straining our eyes in the dark to find patterns in the problem space, and our mind tells us we see shapes. For the moment they appear clear and inevitable, but in the fullness of time they will prove to have been illusions. But making things worse, the shadow you think you see may really exist, it's just not what you thought it was. That's the insidious nature of this noise: what you see may in fact be truth in a grander context. But in our immediate situation, it is irrelevant and problematic.

This concept is admittedly inspired heavily, though indirectly, by Raganwald's concept of "incidental complexity", where a solution takes a cumbersome form because of the act of projecting it upon the surface of a particular programming language, not unlike the way the picture from a digital projector becomes deformed if you point it at the corner of a room.

The real and serious implication of this is that, to put it in Raganwald's terms, if you refactor an incidental redundancy, the message your solution ends up sending to other programmers, and to yourself in the future, ceases to be useful in understanding the problem that is being solved. It starts sending a signal that there is a real and important correlation between the two things that you've just bound up in one generalization. When in fact, it's just chance. And so when people start to build on top of that generalization with those not quite correct assumptions, unnecessary complexities can quite easily creep in. And of course that inevitably impacts maintenance and further development.

Noise is ever-present in the world of programming, as in other creative and engineering disciplines. But it doesn't just come from the intrusive environment of our programming language or our tools as Raganwald pointed out. It can come from our own past experience, and even come from the problem itself.

So be wary. Don't submit unwittingly to the siren song of one more redundancy elimination. Think critically before you click that "refactor" button. Because eliminating an incidental redundancy is like buying those "as seen on tv" doodads to make your life "easier" in some way that was somehow never an issue before. You think it's going to streamline some portion of your life, like roasting garlic or cooking pastries. But in your quest to squeeze a few more drops of efficiency out of the tiny percentage of your time that you spend in these activities, you end up out some cash, and the proud owner of a toaster oven that won't cook anything flat, or yet another muffin pan, and a bunch of common cooking equipment that you probably already own.

So remember, redundancy should always be eliminated, except when it shouldn't. And when it shouldn't is when it is just noise bubbling up from your own mind, or from the problem space itself.

The First Rule of Extension Methods

Extension methods are a tremendously useful feature of C# 3. Briefly, they allow you to bundle new behavior into an existing class that wasn't included by the class's original author, but without opening up the implementation internals of the class. In a very general sense, this is useful if you come up with useful behavior related to a class and the best place for it is IN that class, but you don't want to bend or break encapsulation by inheriting. I won't spend any more words on an introduction, but rather offer a caution, for those of you who have seen their usefulness and would like to start taking advantage.

Before you even begin to think about whether a particular behavior belongs on an existing class, or as a service, or what have you, you should internalize one cardinal rule of dealing with extension methods. Thankfully this First Rule of Extension Methods is nothing like the First Rule of Fight Club, because if it were, I wouldn't be able to help you at all. No, the First Rule of Extension Methods is: DO NOT export extension methods in the same namespace as your other public classes.

The reason for this is very very simple: odds are very good that if you have come up with an idea of including a particular new behavior on an existing class, someone else has or will as well. There will only be a finite number of relevant names to give this new method, which means that if it's a simple method, especially one without parameters, there's a decent chance that the signatures of your method and this other programmer's will be identical. And if both you and this other programmer happen to include the method on public static classes in a namespace with other functionality the user needs, then someone trying to use both libraries could very likely run up against identifier collisions with the two methods.

Note that the rule begins with "do not export..." This is important, because you can be 100% certain to save your users any collision headaches if you just don't export your extension method. Why wouldn't you export your extension method? Well, there's a very good chance that just because you found your extension method to be useful and, dare I say, clever (Tyler Durden: "how's that working out for you?"), that doesn't mean the consumer of your library will. So consider carefully whether you should even make the method public at all, or rather just keep it internal.

If you decide that your method is just so darned handy that to keep it locked up would just be sadistic, then make a separate namespace for each batch of related extension methods you want to export. If the user decides they'd like to use them too, they can import the namespace as necessary. This will minimize the chance that they will need to fully qualify the namespaces of the other library with the identically named method whose author wasn't as responsible as you were and polluted their namespaces with extension methods.

This tactic won't guarantee anything, because there's always a chance some other library could use the same namespace identifiers as well. But with each additional namespace, you dramatically increase possible naming permutiations, and proportionally decrease the chance of collisions.

Useful Extension Methods 1 through 3 of N

Quite often when I'm writing code I'll notice a very small bit of logic that keeps popping up all over the place. It's usually something so trivial that most people barely notice it. But it's also usually something that shows up so often that, despite being small and ignorable, it constitutes a fairly constant level of noise in the code. By noise I simply mean something that takes up more characters than it needs to, obscuring the real meat of the logic of your code. Common functionality like this that everyone knows and understands should just get out of the way, fade into the background, and let the unique logic stand out.

You may have also heard of this noise idea by another name: accidental complexity.

As Reg Braithwaite has pointed out, looping syntax is one of these things. With the ubiquity of IEnumerable and the advent of extension methods in C#, there is almost never a good reason to write an explicit for loop anymore. Looping is a ubiquitous bit of logic that nonetheless takes up quite a lot of characters. Even the vaunted foreach loop is now officially more verbose than it very often needs to be.

Microsoft made it easy to get rid of the explicit loop when what you are doing is essentially a mapping operation, with the inclusion of the IEnumerable.Select extension method.

Say your Foo class has a static function taking a Bar and returning a Foo, and you want to use this function to take a collection of Bars and create a collection of Foos.

You could do this:

IEnumerable<Bar> bars = GetAllBars();
List<Foo> foos = new List<Foo>();

foreach (var bar in bars)
foos.Add(Foo.FromBar(bar));

Or you could do this, which is obviously much more concise:

IEnumerable<bar> bars = GetAllBars();
IEnumerable<foo> foos = bars.Select(Foo.FromBar).ToList();

Note that the Select function completely takes care of the looping logic. Once you know that, this code reveals itself as being extremely elegant. But what if the action you're taking doesn't return anything? You're "stuck" writing an explicit loop, right? Not at all.

Take this code:

IEnumerable<Foo> foos = bar.GetAllItems();

foreach (var foo in foos)
PrintToScreen(foo);

To start removing the noise, first define an extension method for IEnumerable called ForEach. This is extension method #1.

public static IEnumerable<X> ForEach<X>(this IEnumerable<X> lhs, Action<X> func)
{
foreach (X x in lhs)
{
   func(x);
   yield return x;
}
}

Then rewrite:

bar.GetAllItems()
.ForEach(PrintToScreen)
.ToList();

Now there's just the issue of that nasty little ToList call. Right now, we need that in order to force the collection to be iterated. The yield return syntax essentially causes a function's execution to be deferred until an element is actually requested. This is actually potentially useful even if none of the things you need to do will return values. You can chain together a bunch of actions on the collection by chain-calling ForEach with different delegates. But it's still silly to create and throw away a List just to do this.

So we create an Evaluate function that does a simple explicit iteration and nothing more, to force the iterator to be evaluated. This is extension method #2.

public static void Evaluate<X>(this IEnumerable<X> lhs)
{
 foreach (X x in lhs) ;
}

And now you can replace ToList with Evaluate, which will iterate the collection without allocating a new List.

bar.GetAllItems()
.ForEach(PrintToScreen)
.Evaluate();

This is nice, and is going to be useful if we need to chain ForEach calls. But when we don't need that there's still that Evaluate call at the end that's going to be repeated every time we want this functionality, which could be an awful lot. So, let's get rid of that too.

To do that we define a Visit function (named for the Visitor Pattern), that will call ForEach with the given delegate, and then Evaluate as well. This is extension method #3.

public static void Visit<X>(this IEnumerable<X> lhs, Action<X> func)
{
  lhs
      .ForEach(func)
      .Evaluate();
}

Now we can finally get all this done in a single function call:

bar.GetAllItems()
  .Visit(PrintToScreen);

This takes some getting used to. But it really has the potential to condense your code. It isn't readily apparent looking at one bit of code, but once you start talking about nested loops or consecutive loops, you'll see the difference. Not to mention the total effect it will have across your codebase. Loops are everywhere. Shave off 50 characters from each one and your talking about a lot of characters in aggregate.

For my part, after I determined to avoid explicit loops whenever possible, the comparatively verbose explicit looping syntax became almost painfully extraneous to my eyes. I feel like function calls are much more elegant.

Decoupling Domain Model from Persistence

For the last several months, I've been working on a Windows desktop application. This application has a number of pretty common aspects: file manipulation, local data repository, GUI, user settings, collection/dataset manipulation (think drag-and-drop listview type stuff), communication with peripheral devices, and communication with remote services (such as a web service). I think just about every desktop application has a good cross-section of these aspects, and maybe a few others that are slipping my mind at the moment. As a result, there are patterns of application architecture that will arise, and which the development efforts of well-designed, robust applications will have in common. I'm not talking about the typical "design patterns" here à la Gang of Four (GoF), but rather "application architecture patterns". Big patterns. A set of 4 or 5 patterns that, when meshed together, encompass the big, meaty chunks accounting for 95% or better of your application.

I know this is true. I know these patterns exist. But as this is my first effort in developing a desktop app of this complexity, I don't really know what the patterns are. One that GoF did account for was MVC/MVP, and sure I know those... But honestly, up until recently (and maybe even still) my knowledge of that pattern was very hazy and academic. Actually implementing it was something I'd never had to do before. It took a lot of blood, sweat, and tears--lots of trial and error--to get to a point where I really feel like I'm starting to grasp the "right" way to put together an MVP structure.

So now I've moved on to persistence. I have my domain model. But I need to be able to persist the objects in my domain model to and from disk (not a database!). I've been struggling to find ways to add in this functionality without tainting the domain model with persistence logic. Granted, this is a valid way of doing things, as is evidenced by Martin Fowler's ActiveRecord pattern. But it really doesn't make for ease of unit testing. Your business logic and persistence logic get all mixed up in the same classes and you can't easily isolate one from the other for testing purposes.

Then I saw Fowler's Repository pattern. I thought, okay, maybe that will help. I can create an interface that I can implement which will take care of all the logic for disk access to all the right places, based on what objects or collections are being retrieved. And I can just mock the interface for purposes of testing the domain model and business logic. I have a simple three-level hierarchy of domain interfaces, so it would be fairly simple to implement all the querying and CRUD I need for each domain class on the repository interface. But then I thought about how we plan to have multiple implementations of these interfaces in the future, with different permutations of under-the-covers data to be persisted, and thought maybe it would be best to have the repository be metadata-driven, rather than hard-coding the query logic for the different domain classes. This of course naturally leads to a record-based design, and that would mean I'd want data mappers to translate from my domain classes to repository records. And of course, the repository class should be strictly independent of the persistence mechanism itself (in this case the disk) so that I can unit test the repository logic without worrying about maintaining a test repository just for that purpose.

And suddenly I realized that I had mentally re-created ADO .NET. DataSets and DataTables are the repository mechanism, (with typed datasets and the ADO designer even supporting generating data mappers for you). DataAdapters are the persistence service.

So where this leaves me is with the question of whether I should just design my on-disk storage schema, build myself an app-specific data adapter mechanism, and let ADO .NET do all the work. If I really wanted to minimize the amount of mapping and repository-access code I have to write, I might even be able to use the Entity Framework to do my dirty work for me. Admittedly I have no idea how much work it would take to implement my own data adapter. The interfaces seem straightforward enough, but I have a nagging feeling that's really just the tip of the iceberg.

After all my radio silence here, I don't know if anyone is still listening... But if anyone has any thoughts on the wisdom of this approach, I'm listening intently.

Don't Give Up Assembly Privacy For Sake of Unit Testing

Just a little PSA to other .NET unit testing newbs out there like me. This info is available various places on the internet, but you'll be lucky to find it without just the right search terms. So hopefully adding another blog post to the mix will make it easier to stumble on.

Unit testing frameworks need to instantiate your types, in order to run unit tests. What this means is that they need to be able to see them. The easiest way to do this is to make your classes public and/or place the tests right inside your project.

Placing the tests right in your project means that you'll very likely have to distribute the unit test framework assemblies along with your product. This might give more information to potential hackers than you would like. And making your classes public brings with it the often undesirable side-effect of opening up essentially all the types in your assembly to be used by anyone who knows where the assembly file is, in essentially any way they like.

But you don't have to make these concessions. You can move the tests out of your assembly, to keep them out of the deployment package, and still keep your classes internal (though not private). The .NET framework allows an assembly to declare "friend" assemblies that are allowed to see its internal classes. (Yes, very similar to the old C++ friend keyword). This is accomplished by adding an assembly attribute called InternalsVisibleTo to your AssemblyInfo.cs file.

If your unit test project does not have a strong name, it's as simple as referencing its assembly name:

[assembly: InternalsVisibleTo("MyCoolApp.UnitTests")]

However, I strongly recommend giving your unit test assembly a strong name. A strong name is a name involving a public-private key pair, and which is used by the .NET framework along with some hashing and encryption technology to prevent other people from creating assemblies that can masquerade as your own. Furthermore, if you give your app itself a strong name (which you should if you plan to distribute it), any libraries it references will need strong names, including the ones it just allows to see its internals.

So, if you decide to give your unit test project a strong name, you'll need the public key (not just the token) as well:

[assembly: InternalsVisibleTo("MyCoolApp.UnitTests, PublicKey={Replace this, including curly braces, with the public key}")]

(If you need to learn about strong names, and/or how to extract the public key from your assembly, this is a good place to start: http://msdn.microsoft.com/en-us/library/wd40t7ad.aspx.)

Once you've done this, you should be able to compile and run your unit tests from a separate project or even solution, and still keep the classes you're testing from being "public".

This is all well and good, but if you're working with mocks at all, you probably have another problem on your hands. The most popular .NET mock frameworks (e.g. RhinoMocks, Moq, and NMock) use the Castle Project's DynamicProxy library to create proxies for your types on the fly at runtime. Unfortunately, this means that the Castle DynamicProxy library ALSO needs to be able to reference your internal types. So you might end up with an error message like this:

'DynamicProxyGenAssembly2, Version=0.0.0.0, Culture=neutral, PublicKeyToken=a621a9e7e5c32e69' is attempting to implement an inaccessible interface.

Complicating this fact is that the Castle DynamicProxy library places the proxies it generates into a temporary assembly, which you can't just run the strong name tool against, because the temporary assembly doesn't exist as a stand-alone file. Fortunately, there are programmatic ways of extracting this information, and the work has been done for us. The public key for this assembly, at the time of this writing, has been made available, here and here. You might find some code at those links that could help you extract the public key from any future releases of Castle as well.

The important information is basically that, as of today, you need to add this to your AssemblyInfo.cs file, without line breaks:

[assembly: InternalsVisibleTo("DynamicProxyGenAssembly2, PublicKey=002400000480000094000000060200000024000052534131
0004000001000100c547cac37abd99c8db225ef2f6c8a360
2f3b3606cc9891605d02baa56104f4cfc0734aa39b93bf78
52f7d9266654753cc297e7d2edfe0bac1cdcf9f717241550
e0a7b191195b7667bb4f64bcb8e2121380fd1d9d46ad2d92
d2d15605093924cceaf74c4861eff62abf69b9291ed0a340
e113be11e6a7d3113e92484cf7045cc7")]

Caution: The name and public key of this temporary assembly was different in earlier versions, and could change again in later versions, but at least now you know a little more about what to look for, should it change.

So remember: You don't have to open wide your assembly to just anyone who wants to reference your types, just for sake of unit testing. It takes a bit of work, but you don't need to compromise.

Surviving WinForms Databinding

I've rarely had the freedom in my career to implement a Windows application using MVC-style separation of concerns. Generally I am told "just get it working". Now, if I already knew how to tier out an application, this wouldn't be a problem. But since I don't, and it would take me a good deal of time to figure out a satisfactory way of doing it, I haven't been able to justify spending the time, on the company dime.

But recently, I've been fortunate enough to work on a new software product without a hard ship-date, and having other obligations on my plate. This has given me the freedom to not spend every minute producing functionality. So I've been experimenting with implementing MVC with Windows Forms.

There are essentially two ways to get this done. You can:

1. Write a bunch of manual event code to trigger view changes from model changes, and vice versa.
   
2. Use databinding and save yourself the explicit event code.

This works great if all your datasources are DataTables, or DataViews, or other such framework classes that are designed from the ground up to work with WinForms databinding. But should you have the misfortune of not dealing with any record-based data, you'll find you have a much tougher road to walk.

If you, like I, choose option 2, and you happen to be working on anything more complicated than a hello world application, and you are truly committed to doing MVC both correctly, and with as little unnecessary code as possible, then you will undoubtedly spend, like I have, a lot of time banging your head against a brick wall, trying to figure out why your databinding isn't doing what it is supposed to. This is a terrible shame, because if databinding in WinForms worked properly and was easy to use, it would be a spectacular tool for saving time and shrinking your codebase.

Truth is, you can still same time and code. But not as much as you might think when first introduced to the promise of databinding. If you can find any decent information on the obstacles you'll encounter. Compounding the above hurdles is the fact that what information can be found online about them is scattered to the four winds, and no one bit references the rest. So, I've decided to blog the headaches I encounter, and my resolutions, as I find them. This should increase the searchability of the issues at least a bit, by tying together the separate references with my blog as a link between them, and also by containing the different bits of information within one website. Or it would, if I had readers...

My results so far have produced 5 rules, to help you preserve your sanity while using WinForms databinding.

Rule 1: Use the Binding.Format and Binding.Parse events.

This first rule isn't actually too hard to find information on. Format and Parse essentially let you bind to a datasource property that doesn't have the same data type as the property on the control. So you can bind a Currency object to a TextBox.Text property, for example.

The Format event will let you convert from your datasource property type to your control property type, and Parse will let you convert from your control property type to your datasource property type. The MSDN examples at the links above are pretty good. If you use them as a template, you won't go wrong. But if you start to switch things up, beware Rule 2...

Rule 2: If you use Format or Parse events, DO NOT add the Binding to the control till after register with the events.

I honestly don't know what the deal is with this one. I just know that if you add your events to your Binding object after you've already passed it to the Control.DataBindings.Add function, they won't get called. I don't know why this should be, unless the control only gets a copy of your actual Binding object, not a reference to it.

Unfortunately, I have lost the references I had to the forum posts that talked about this. There were several, and now I can find none of them. I know I saw them, though, and I saw the symptoms of the other ordering, so as for me, I'm going to make sure to follow this rule.

Rule 3: Use INotifyPropertyChanged and/or INotifyPropertyChanging.

I ran across this info in a post on Rick Strahl's blog. I ran across this information during a desparate scramble to find out why my datasource ceased to be updated by user actions on the controls, after the initial binding occurred. The INotifyPropertyChanged interface is intended to be implemented by a datasource class that has properties that will be bound to. It provides a public event called PropertyChanged, which is registered with the data binding mechanism when you add the Binding to your Control. Your class then calls this event delegate in the desired property setters, after the new property value has been set. Make sure to pass "this" as the sender, and the name of the property in the event arguments object. Notice that the property name is provided as a String, which means that there is reflection involved. This will become relevant in Rule 4. Also note that there is an INotifyPropertyChanging interface, which exposes an event that is meant to be raised immediately before you apply the datasource change. This is generally less useful for databinding, but I include it here to save some poor soul the type of frustration I have recently endured.

Rule 4: If you implement INotifyPropertyChanged, don't include any explicit property change events ending with "Changed".

As I mentioned, the databinding mechanism uses reflection. And in so doing, it manages to outsmart itself. There is a very good chance you're going to run into a situation for which these databinding mechanisms aren't useful, and you'll have to implement your own explicit property change events on your datasource class. And of course, you're going to name these events in the style of "NameChanged", "AddressChanged", "HairColorChanged", etc. However, the binding mechanism things it's smart, and rather than just registering the INotifyPropertyChanged.PropertyChanged method, it will also register with any public event whose name ends with "Changed". And if you didn't happen to make your event follow the standard framework event signature pattern--that is, void delegate(Object sender, EventArgs e)--then you will get errors when the initial binding is attempted, as the mechanism attempts to register it's own standard-style delegates with your custom events, and you get a casting error.

I solved this one by following a crazy whim, but I also tried to verify the information online. All I could find was one old post buried in an obscure forum somewhere.

Rule 5: Don't bind to clickable Radio Buttons

I know how great it would be if you could just bind your bunch of radio buttons to an enum property. I really do. You think you're just going to hook up some Format and Parse events to translate back to your enum, and all will be well. It would be so darn convenient, if it actually worked. But WinForms just isn't cut out for this. For 3 full releases now (or is it 3.5 releases?), this has been the case. It's because of the event order, which is not something that MS can go switching up without causing thousands of developers to get really cheesed off.

The problem really comes down to the fact that unlike other controls' data properties, the Checked property of a radio button doesn't actually change until focus leaves the radio button. And as with all WinForms controls the focus doesn't actually leave the radio button until after focus is given to another control, and in fact not until after the Click event of the newly focused control has fired. The result of this, as it pertains to radio buttons, is that if you try to bind to them, the bound properties in your datasource will actually lag your radio buttons' visual state by one click. If you have just two radio buttons, the datasource will be exactly opposite the visible state, until you click somewhere else that doesn't trigger an action that references those datasource properties. Which can make this a really infuriating bug to track down. I almost thought I was hallucinating.

Now, in all honesty, it's possible to make it work. But it is the kludgiest kludge that ever kludged. Okay maybe it's not that bad... but it's a messy hack for sure. It takes a lot of work for something that really should already be available. As near as I can tell, the only way to solve this problem without giving up the databinding mechanism is to essentially make your own RadioButton control, with a property change and event order that is actually useful. You can either write one from scratch, or sub-class RadioButton and override all the event logic with custom message handling.

So....

There's the result of 3 weeks of frustration. I hope it helps someone else out there someday. I'll make list addendum posts if/when I come across any other mind-boggling flaws in the WinForms databinding model. And in the meantime, I welcome any additions or corrections that anyone is willing to contribute in the comments.

Is There a Place for Deletionism in Wikipedia?

Just dipping a toe in the water with something too big for Twitter, but that I definitely have a few thoughts on which I am willing to pitch out onto the internet.

Yesterday evening and this morning I watched (Or overheard? No idea what the appropriate term here is...) an exchange over Twitter between Tim Bray and Jeff Atwood about "deletionism". Tim's thoughts on the matter were apparently too strong to be held within the restrictive confines of Twitter and so he wrote a strongly worded post on his blog as well.

The post is obviously... passionate. But putting aside the bulk of the post that simply expresses that passion, he makes a couple really strong points.

The first point is that deletionists are just your garden variety elitists.

"the arguments from the deletionists are jargon-laden (hint: real experts use language that the people they’re talking to can understand)"

The other point really could have comprised the whole post and, IMHO, would have been a sufficient argument all by itself.

"What harm would ensue were Wikipedia to contain an accurate if slightly boring entry on someone who was just an ordinary person and entirely fame-free? Well, Wikipedia’s “encyclopedia-ness” might be impaired... but I thought the purpose of Wikipedia was to serve the Net’s users, not worry about how closely it adheres to the traditional frameworks of the reference publishing industry?" [emphasis added]

This, to me, undermines the deletionists' whole platform. That is what Wikipedia was supposed to be: a new model of information archival. A model not subject to the sensibilities of some authoritarian arbiters of what is "notable" or "interesting". And the deletionists are unequivocally trying to undermine this goal, by deciding what "deserves" to be archived.

I say, if they want to take that old dead-tree encyclopedia model and just port it to the web, they can go find their own site, and their own content, to do it with. I've even got a couple recommendations for them.

Identity Crisis in Computer Science Education

A while back, the seeds of a post started rolling around in my head, inspired by my lack of satisfaction with the preparation my education provided me for a programming career. But I didn't quite know what I thought. Then not long ago, Joel Spolsky presented a radical repackaging of Computer Science degrees, supposedly geared toward producing better programmers, and my thoughts started to gel.

I knew what my personal complaint was, and I knew that it was connected to a larger problem with the state of computer science education in general. But I didn't know exactly what the larger problem was, let alone have any ideas worth sharing on what might be done about it.

Now that seemingly the entire remainder of the blogosphere has weighed in on this and related topics, I think I am finally ready to throw my two cents in. I'm going to barrage you with links in the following paragraphs, to ensure that I credit everyone I read who assisted me in coming to my final conclusions. Feel free not to click through, but be aware that they represent a rich cross-section of an important discussion.

It took me several weeks to realize that what we have going on is essentially a three-way tug of war from people in different regions of the vast sphere of software development, who need very different things out of their workers, and hence out of their education. Below I will give a run-down of some of the claims made, expressing the different forces pulling on CS graduates these days. You'll quickly see it's no wonder that the schools are so confused....

The Artisan Programmer

Joel laments the uselessness of theory courses in computer science curricula, saying "I remember the exact moment I vowed never to go to graduate school" and then proceeding to recall a terrible experience he had with a Dynamic Logic class. Jeff Atwood insists that real-world development environments need to be in place and mandatory, including, but not limited to, source control, bug tracking, deployment, and user feedback. Then, as mentioned above, Joel proposes offering BFAs in software development, to make darn well sure that none of the academic (in the pejorative sense) theory stuff gets mixed in unnecessarily. The upshot of most of these points are that computer science / programming degrees should spend as much time as possible teaching people what they need to know to go into a career in software development, writing business software or software products.

The Computer Scientist

Brian Hurt comes in from another direction entirely, and in the process makes some very good points about the true purpose of higher education. He lays the blame for the flood of single-language programmers entering the workforce at the feet of schools who do just exactly what Joel and Jeff are asking for. He makes some great points. And while he sounds more than a little reminiscent of the classic Joel post about the perils of java schools, his argument is much more thorough than just blaming the tools. Chris Cummer joins this party, wishing that his theory foundations had been firmer, and making an excellent analogy to the difference between someone who studies a language, and someone who studies language. We also have the respectable Raganwald, who although he has admirably pointed out good points from all sides, doesn't shy from offering his opinion that programmers ignore CS fundamentals at risk of their own career advancement.

The Software Engineer

But thats not all. Several people have weighed in from yet another direction. Robert Dewar and Edmond Schonberg wrote one of the posts that started off this blog firestorm. Along with alluding to a similar sentiment as Hurt and Cummer, they heavily criticize the state of software engineering education for focusing too much on how to use specific, limited tools, when there are more sophisticated ones available. They claim understanding these will allow software engineers to easily pick up the other tools that may come along and direct them to appropriate purposes. Ravi Mohan stops short of calling the education satisfactory, instead sensibly pointing out simply that an engineer who doesn't use standard engineering tools such as system modeling, isn't really an engineer. Mohan comes on a little too strong for me in the comments, but the posts themselves (of which there are also a precursor and a successor, and should soon be one more) are worth reading. Like the others he makes valid points.

Resolving the Crisis

Mark Guzdial is one of the few people that really puts his finger near the pressure point. Though maybe not near enough to feel the pulse beneath it when he did so. At risk of quoting a little too heavily....

Rarely, and certainly not until the upper division courses, do we emphasize creativity and novel problem-solving techniques. That meshes with good engineering practice. That does not necessarily mesh with good science practice.

Computer scientists do not need to write good, clean code. Science is about critical and creative thinking. Have you ever read the actual source code for great programs like Sketchpad, or Eliza, or Smalltalk, or APL 360? The code that I have seen produced by computational scientists and engineers tends to be short, without comments, and is hard to read. In general, code that is about great ideas is not typically neat and clean. Instead, the code for the great programs and for solving scientific problems is brilliant. Coders for software engineers need to write factory-quality software. Brilliant code can be factory-quality. It does not have to be though. Those are independent factors.

And there it is.... Different environments require different mindsets/approaches/philosophies. Research requires one mindset/philosophy of work, engineering requires another, and in-the-trench-based programming requires yet a third.

When a person suffers from a personality fracture, the resolution is often to merge the personalities by validating each as part of a whole. Fortunately, since we are not dealing with a person, we have the freedom to go another direction: make the split real and permanent.

Associate of Science in Computer Programming

To fill Joel and Jeff's need, the student who wants to work in the craft of software development / computer programming, who wants to be an artisan, needs to have an appropriate degree. It needs to provide them with an exposure to the generalized idea of the programming platforms and tools that they will have to deal with for the rest of their career. Lose the lambda calculus, compiler-writing projects, etc. These things not necessary for them to get stuff done in the trenches. But they do need to be exposed to the fundamental generalities that pervade programming. And they need to be prepared to learn at an accelerated rate while in the field. That just comes with the territory. Focus on core programming skills like program analysis, debugging, and test practices. Introduce industry-standard tools (emphasizing generality and platform-independence) such as source-control, bug tracking, etc.

I think a two-year associate degree is perfect for the code-monkeys and business programmers that just love to dig in and mess around with code, and don't want to concern themselves with the overarching concerns. Especially with these jobs increasingly being pushed offshore, computer science grads are rapidly being priced out of the market. An associate degree is cheap enough to be worth the investment for a lower-paying programming job. And it doesn't carry the overhead of any unnecessary theoretical content that they may not be interested in learning. It should be noted though that this type of programming job enters the realm of the trades, with all the associated benefits and drawbacks.

If you're looking for a more well-rounded individual capable of moving up out of this position into a lead position, or even management, then a 4-year bachelor of science (or Joel's BFA, but I tend not to think so) may be a viable option as well.

Bachelor of Science in Computer Science

There's not much to say about this degree, because if you look at all the schools that are famous for their CS degrees, this is pretty much what you'll find. Lighter on general studies, heavy on theory, heavy on math. Light on tools because the students will be expected to find (or make) tools that work for them. Light on specific language education because students will be expected to adapt to whatever language is necessary for their problem domain.

This is a degree that will produce people primed for going on to masters and doctorates. They will end up in research, "disruptive" startups, or working on new languages, OSes, etc. This degree is designed for people who want to work at the edge of things. Who want to solve new problems and push the boundaries. They are people upon whom will be placed the burden of pushing the state of knowledge in CS into the next era.

Bachelor of Science in Software Engineering

I am hesitant to propose this degree, because I am not certain that the practice of Software Engineering has evolved to the point where we have 4 years worth of general knowledge that's worth teaching, and that won't be out of style by the time the student's graduate.

It seems that some people, when they talk about Software Engineering, are talking about architecture and design, and others are talking about process, resource allocation, estimation, etc. To be frank, I don't think the former qualifies as a true engineering discipline. At least not yet. I don't know how much the modeling of programs that Ravi Mohan talks about is going on out there in the industry. I suspect that it happens more in the process of really big projects, and maybe in digital security. The second type of engineering people think of, however, I think is very similar to what we see in manufacturing, with industrial and process engineers. These are people who get an intimate knowledge of the domain, and then figure out ways to get everything to run smoother, more efficiently, and producing higher quality.

I can definitely see some education possibilities here, though I am not sure myself how to fill out the whole degree. It should at least encompass a good portion of the Associate of Science in Computer Programming, because they need to understand the intricacies involved. I can also see this degree teaching some of the more established measurement and estimation techniques found among the industry's established and experienced software project managers. Generally more management-related topics such as resource allocation, planning, product design, feature negotiation, etc. might fit in well here. Different project processes, testing/QA models, and of course an ability to keep up to date with technologies and platforms, are all par for the course as it's all critical for making decisions in the industry.

Conclusion

I really, honestly believe that Computer Science education as a whole needs a makeover. It needs more structure, more integrity in the vision of what each degree means, across schools. When someone has one of these degrees, you need to be able to reliably assume they should have learned certain things, regardless what school they went to. Many of the degrees currently on offer don't satisfactorily prepare their students for any one of the possible careers discussed above. I'm not saying their hand needs to be held from enrollment right on through to their first job. That's not the purpose of college. The purpose of college is to provide a cohesive education, directed to some relatively well-defined goal of capability and knowledge. Today this is tragically non-uniform at best, and absent altogether at worst.

So I see plenty of room in software development education for a clarification of purpose, and a readjustment of goals and curricula. A few different tracks, each geared toward a distinct section of the sphere with different goals and different responsibilities. And if we resolve to use existing terminology with some respect for the historical meaning of the words, we can re-use our existing nomenclature. But there can be no more of this muddy slurry of computer science, craft of programming, and software engineering all overlapping in claims of purpose, treading on each others' territory without care. Everyone can have what they are asking for. They just need to accept that no one can claim the "one true way".

I am not a Computer Scientist

Prepare yourselves. I have an embarrassing and melodramatic admission to make.

My career is a sham.

Although my degree and education are in a field that is typically referred to as "computer science". I am not actually a "scientist". Nor do I "practice science". But I won't be satisfied to go down alone for this charade. I'll going on record saying that I am convinced that for the vast majority of people who were educated in or work in the field of "computer science", the ubiquitous presence of the word "science" in proximity to our work or education, is a tragic misnomer.

I don't know how long this has been on my mind, but I know almost precisely when I became conscious of it. It was a couple months ago. I was newly exposed to devlicio.us, and perusing the blogs hosted there, when I came across a post by Bill McCafferty about a lack of respect and discipline in our field.

Early in the post, Bill reveals an injustice he encountered during his education.

...When I started my undergrad in this subject, I recall reading articles debating whether it should be called a science at all. Gladly, I do not see this argument thrown around much anymore.

I think I am probably not going to make the exact argument here that he disagreed with back then. The things we all studied in school are definitely part of a nebulous field of study that may rightfully be called "computer science". As Bill points out,

"From Knuth's classic work in The Art of Computer Programming to the wide-spread use of pure mathematics in describing algorithmic approaches, computer science has the proper foundations to join other respected sciences such as physics, concrete mathematics, and engineering. Like other sciences, computer science demands of its participants a high level of respect and pursuit of knowledge."

I have no argument with any of this. He's right on. Donald Knuth (who is indeed my homeboy in the sense that we share our hometown) studied and practiced computer science (which if you know anything about Knuth, you'll know is an almost tragic understatement). And thousands of people who have followed in Knuth's foot steps can lay the same claim. However, that's not me. And it's not more than 99% of all programmers in the field today.

Computer science suffers the same type of misnomer as many other disciplines who have adopted the word "science" into their name, such as political science, social science, animal science, food science, etc. And it seems that most such fields, if not all, have done so because the very validity of the field of study itself was subject to severe criticism at some point in the past. So we take on the term "science" to get it through people's heads that there is a root in formal practices and honest intellectual exploration. But to then blanket every profession that derives from this root with the term "science" is a misappropriation of the term.

I can think of a number of examples.... The programmer working for the bank to develop their website, or for the manufacturing company to manage their transaction processing system is no more necessarily a "computer scientist" than the election commentator is necessarily a "political scientist". When someone gets an electrical engineering degree and goes to design circuits for a living we do not say he "works in electrical science". We say he is an electrical engineer. When someone gets a technical degree in mechanics and then goes to support or produce custom machinery, we do not say he "works in mechanical science". We say he is a mechanic, or a technician. Why, then, when someone gets an education that amounts to a "programming degree", and then goes to work doing programming, do we say that he "works in computer science"? It's a uselessly vague and largely inappropriate label.

By contrast, if you have a doctorate in computer science, I'm prepared to say you deserve the label. If you write essays, papers, articles, books, etc. for use by the general practitioner, you probably deserve the label. If you do research, or work on the unexplored fringes of the field--if you are exploring the substance and nature of the information or practices that the rest of us simply consume and implement, then in all likelihood you deserve the label.

Please, please understand that I am by no means belittling the value of our work, or the nobility of our profession. Often we simply consume the information produced by true "computer scientists". But we transform it from theory into practice. We resolve the concrete instances of the abstract problems that the true scientists formally define. We take the pure thought-stuff produced by scientists and turn it into tangible benefit.

This is not trivial. It is not easy. It deserves respect, discipline, study, and care. But it is not "practicing science".

I should say in closing that I am not as upset about all this as the tone of this post might imply. I don't even really have a big problem with the use of the word "science" to refer to a field of study or work that largely does not include research-type activities. I don't like it, but I accept that it happens. But "computer science" has a problem that other similar "sciences" don't. When someone says they work in "political science" or "food science", you can make a guess as to the type of work they do, and it's hard to be significantly incorrect. Though maybe it's my outsider's naïveté that allows me to make this claim. At any rate, "computer science" as a field is so broad and vague that I don't think the term communicates a useful amount of information. But you wouldn't know that by talking to programmers, who seem only too ready to attempt to take hold of the term and own it for themselves.

I think this is one small facet of a larger and far more critical issue in our field in general, which I fully intend to write more about very soon. But until then, lets take the small step of starting to consider what we really mean when we use much of the popular but often ambiguous terminology when discussing our profession.

I work in the field of computer science. This tells you nothing except that I am unlikely to be a prime specimen of the wondrous human physiology. But.... I am a programmer. I have a degree in Computer Engineering. I am interested in programming theory. I work as a software development consultant. And now, you know something about what I know and what I do.

Now what about you?

Update: I forgot to note that in McCafferty's blog entry, he himself makes use of "trade" terminology to categorize different levels of reading materials. Which belies the uncertain nature of programming as a profession. We certainly wouldn't say that a carpenter works in the "wood sciences", would we?